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Nonequilibrium phase transitions of a nematic liquid crystal under ac field-driven electroconvection

Physical Review E 2022年第1期106卷 014702-014702页

作者： Jong-Hoon Huh Department of Physics and Information Technology Faculty of Computer Science and Systems Engineering Kyushu Institute of Technology Fukuoka 820-8502 Japan

We report on phase transitions between isotropic and nematic liquid crystal phases in nonequilibrium systems (NESs). ac field-driven electroconvection (EC) provides an NES, which can be well controlled by the voltage V and frequency f; it arises electrohydrodynamically at a threshold voltage Vc. In continuous cooling and heating processes with various rates R, the critical temperature Tc was determined at a critical time tc for phase transitions. Moreover, the morphological and dynamical features in the phase transitions were examined using an electro-optical image processing method. In comparison with an equilibrium system (V=0), two typical turbulent ECs (i.e., NESs), which are called dynamic scattering mode 1 (DSM1 for V>Vc) and DSM2 (for V≫Vc), were examined to understand the nonequilibrium phase transitions. In particular, our results show that in high voltage-induced turbulence (i.e., DSM2), Tc can be determined effectively without considering R; this provides a possibility for a material technology application in nonequilibrium-based circumstances.

关键词： Dissipative dynamics Patterns in complex systems Phase transitions by order Transition temperature Liquid crystals

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The Effect of Digital Marketing on Micro, Small and Medium Enterprise in Indonesia 1

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International Conference on Applied Informatics and Media Design, AIMD 2019

作者： Sasongko, Alvin Igo Widjaja, Gregorius Christian Theodore, Jason Afriliana, Nunik Matsuo, Tokuro Gaol, Ford Lumban School of Information System Bina Nusantara University Jakarta Indonesia Faculty of Engineering and Informatics Universitas Multimedia Nusantara Tangerang Indonesia Computer Science Department Bina Nusantara University Jakarta Indonesia Graduate School of Industrial Technology Advanced Institute of Industrial Technology Tokyo Japan

ISBN: (数字)9783031307690

ISBN: (纸本)9783031307683

Digital Marketing is a product marketing strategy using digital media and internet networks. Nowadays, digital marketing is a necessity for companies that thrive in the digital world. It greatly affects the growth of MSME (Micro, Small, Medium Enterprises) especially when it comes to increasing their sales performance by enhancing their brand awareness through various media or instruments such as a Facebook ad, Instagram advertising, Search Engine Optimization, and Search Engine Marketing. This research is aimed to measure how much impact of digital marketing utilization into Micro, Small, Medium enterprises. On the other hand, it also provides an understanding on what are the best digital marketing method to be utilized in the current situation. The method we used in this paper is quantitative. Data were collected through various questions constructed in an electronic questionnaire. This research provides a reference of digital marketing strategies for Micro, Small and Medium business owners. The result shows that digital marketing has a huge impact on the growth of Micro, Small and Medium Enterprise from increasing sales, increasing brand awareness, and gaining customers based on the data collected from both customer and Micro, Small, and Medium Enterprise players in Indonesia. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Digital storage

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105-GHz Electric Field Visualization by Electro-Optic Imaging system Using Polarization Image Sensor

105-GHz Electric Field Visualization by Electro-Optic Imagin...

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European Conference on Microwave

作者： Kiyotaka Sasagawa Ryoma Okada Maya Mizuno Hironari Takehara Makito Haruta Hiroyuki Tashiro Jun Ohta Division of Materials Science Graduate School of Science and Technology Nara Institute of Science and Technology Japan Radio Research Institute National Institute of Information and Communications Technology Japan Department of Opto-Electronic System Engineering Chitose Institute of Science and Technology Japan Faculty of Medical Sciences Kyushu University Japan

ISBN: (数字)9782874870774

ISBN: (纸本)9798350385892

In this paper, we present a system designed for visualization of high-frequency electric field distributions at 105 GHz. Our approach employs an electro-optic crystal plate as the electric field probe, and the changes in the birefringence distribution induced by the electric field are measured through light. The detection system utilizes an optical system for high-sensitivity polarization imaging, which integrates a polarization image sensor with a uniform polarizer. This system converts the high-frequency electric field signal from the device-under-test into a frequency that the polarization image sensor can detect, employing the optical heterodyne method. The light source is generated by an optical modulator and a semiconductor optical amplifier, enabling the measurement of the 105-GHz electric field distribution with the image sensor. This system paves the way for advancements in next-generation wireless communications through precise high-frequency electric field measurements.

关键词： Optical filters Semiconductor optical amplifiers Image sensors Optical polarization Optical mixing Optical resonators Optical imaging Optical sensors Optical modulation Electric fields

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A Support Tool for Test Case First : * Trial for improving quality of specification document through writing system specifications and test cases concurrently

A Support Tool for Test Case First : * Trial for improving q...

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Asia-Pacific Conference on Software engineering

作者： Taiga Wakamatsu Yutaro Mikaduki Noriyuki Kushiro Faculty of Computer Science and Engineering Kyushu Institute of Technology Fukuoka Japan

ISBN: (纸本)9781665455381

In this study, we proposed test case first as a concept for creating a high quality specification document, and developed a support tool for realizing the concept, which generates test cases from the system specification document automatically. The support tool was applied to a toy example of specification document, and evaluated usability and capability to serve as the tool to improve document quality.

关键词： Toy manufacturing industry Usability Software engineering

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Microwave assisted pyrolysis of biomass feedstock fundamentals and the effect of process parameters - A Review 4

Microwave assisted pyrolysis of biomass feedstock fundamenta...

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4th International Conference on Emerging Electrical Energy, Electronics and Computing, ICE4CT 2022

作者： Hamzah, Husam Talib Veluru, Sridevi Hasan, Hikmat Mohammed Abed, Hayder Yousif Mahdi, Husam Salah Hamdullah, Noor Abdulqader Tukarambai, M. Poiba, Venkata Rao Srikanth, R. Department of Chemical Engineering College of Engineering Andhra University Visakhapatnam India Department of Electrical Engineering Faculty of Engineering Ferdowsi University of Mashhad Mashhad Iran Department of Electrical Engineering University of Technology Baghdad Iraq Department of Computer Science and System Engineering College of Engineering Andhra University Visakhapatnam India Electrical and Computer Engineering School of Engineering and Architecture Altinbas University Istanbul Turkey Department of Chemical Engineering Anil Neerukonda Institute of Technology and Sciences Sangivalasa India

Globally, biomass usage as a supply of non-depletable resources materials used in the production of energy at their rawest state is an issue. Pyrolysis is a method of thermally treating biomass that as a consequence in the formation of liquid, products, both solid and gaseous. Elevated heating is required to transform the complicated composition of the biomass's underlying structure matrix into usable products. Heating with a microwave oven has the potential to become a competitive option. to more traditional methods of heating. Owing to its ease of operation and rapid heating rate, it has recently been widely employed in pyrolysis. The goals of this research are to found the principles of MW-assisted pyrolysis action and to examine some critical issues characteristics of operation that have an influence on the yield of a product. This procedure appears to be governed by a number of operational factors for instance, microwave power and temperature degree, the addition of microwave absorbers and their concentration, initial relative humidity, primary sweep gas flow rate/time spent in residence. © Published under licence by IOP Publishing Ltd.

关键词： Biomass

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Deep learning-based pixel interpolation in spatial-domain phase shifting digital holography

Deep learning-based pixel interpolation in spatial-domain ph...

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2022 Conference on Lasers and Electro-Optics Pacific Rim, CLEO-PR 2022

作者： Kajitani, Shu Takabayashi, Masanori Faculty of Computer Science and Systems Engineering Kyushu Institute of Technology 680-4 Kawazu Fukuoka Iizuka820-8502 Japan Research Center for Neuromorphic AI Hardware Kyushu Institute of Technology 2-4 Hibikino Wakamatsu-ku Kitakyushu Fukuoka808-0196 Japan

We propose to apply deep learning to interpolate missing pixels in interferograms acquired by the spatial-domain phase-shifting interferometry (PSI), and numerically evaluate the quality of object light reconstructed ...

ISBN: (纸本)9798350350012

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Optimizing Optical Signal Quality with Deep Learning Dispersion Compensation at Various Distances

Optimizing Optical Signal Quality with Deep Learning Dispers...

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International Symposium on Communications and Information Technologies (ISCIT)

作者： Muhammad Harry Bintang Pratama Lina Marlina Muhammad Fajar Faliasthiunus Pradipta Shien-Kuei Liaw Masayuki Kurosaki Hiroshi Ochi Grad. School of Computer Science and System Engineering Kyushu Institute of Technology Iizuka Japan Grad. Institute of Electro-Optical Engineering National Taiwan University of Science and Technology Taipei Taiwan

One of the limiting factors in long-distance communication with optical fiber is dispersion. Dispersion causes optical pulses to broaden as they travel through the fiber, leading to intersymbol interference that ultimately degrades the signal quality. To solve this problem, a dispersion compensator is usually applied after a certain distance to bring the broadened signal back to its original form. However, this conventional approach is ineffective in cost and implementation since more compensators should be added for a longer distance. In this paper, we propose a deep learning (DL)-based dispersion compensator as an alternative to the current compensator and supplement the current approach if the distance is very long. The dataset is created from signals obtained through the simulation done in optisystem. Different DL algorithms proposed in this paper can classify the received signals from various distances into binary values without the help of conventional dispersion compensation.

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Single and shift-multiplexing recording properties in self-referential holographic data storage with designed additional pattern

Single and shift-multiplexing recording properties in self-r...

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2022 Conference on Lasers and Electro-Optics Pacific Rim, CLEO-PR 2022

作者： Chijiwa, Kazuki Takabayashi, Masanori Faculty of Computer Science and Systems Engineering Kyushu Institute of Technology 680-4 Kawazu Fukuoka Iizuka820-8502 Japan Research Center for Neuromorphic AI Hardware Kyushu Institute of Technology 2-4 Hibikino Wakamatsu-ku Fukuoka Kitakyushu808-0196 Japan

The reconstruction quality and shift multiplexing properties of self-referential holographic data storage (SR-HDS) with additional patterns which are designed with a target intensity of nonuniform distributions such a...

ISBN: (纸本)9798350350012

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Studying of Machine Learning Models for Forecasting Macroeconomic Indicators 27

Studying of Machine Learning Models for Forecasting Macroeco...

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27th International Conference on Advanced Communications technology, ICACT 2025

作者： Ngoc, Lan Dong Thi Ngo-Thi-Thu-Trang Kim, Kyoung-Mok Pham, Vung Nguyen, Ha-Nam Department of Economic Information System Academy of Finance Hanoi Viet Nam Faculty of Information Technology University of Engineering and Technology Vietnam National University Hanoi Viet Nam Posts and Telecommunications Institute of Technology Hanoi122300 Viet Nam Computer Science Department Sam Houston State University HuntsvilleTX77340 United States Department of Medical Information Sahmyook Health University Seoul Korea Republic of Faculty of Information Technology Electric Power University Hanoi Viet Nam

ISBN: (纸本)9791188428137

This study explores the application of machine learning models in forecasting macro-economic indicators, including GDP, inflation rate, unemployment rate, and exchange rate across 11 Southeast Asian countries. The models used include Linear Regression, ARIMA, Random Forest, XGBoost, LSTM, and SVM. We conducted a performance comparison of each model based on MAE, RMSE, and R2 metrics to evaluate the accuracy of the forecasts. The experimental results indicate that Random Forest and XGBoost models excel in predicting nonlinear and complex indicators such as GDP and unemployment rate, while ARIMA and Linear Regression models perform better in time series with clear regular patterns, like inflation rate. The LSTM model shows inconsistent effective-ness, requiring large data volumes and complex optimization processes. SVM demonstrates potential in handling nonlinear data but requires careful tuning. This study concludes that using machine learning models presents significant potential for improving the accuracy of macroeconomic forecasting. However, model tuning and optimization are essential to match the characteristics of each type of economic indicator. Future research directions include developing hybrid models and integrating additional factors such as market sentiment, social and environmental indicators (ESG) to enhance forecasting outcomes. Copyright 2025 Global IT Research institute (GIRI). All rights reserved.

关键词： Inflation

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Front-light Structure for a Lensless Fluorescence Imaging Device with a Hybrid Emission Filter

Front-light Structure for a Lensless Fluorescence Imaging De...

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IEEE Biomedical Circuits and systems (BIOCAS)

作者： Kiyotaka Sasagawa Yuki Ito Daniel Schaeffer Yoshinori Sunaga Hironari Takehara Makito Haruta Hiroyuki Tashiro Jun Ohta Department of Materials Science Graduate School of Science and Technology Nara Institute of Science and Technology Nara Japan Deggendorf Institute of Technology Deggendorf Germany Department of Opto-Electronic System Engineering Faculty of Science and Engineering Chitose Institute of Science and Technology Department of Health Science Faculty of Medical Sciences Kyushu University

Lensless optical imaging is extensively used for deep brain imaging. In this study, we propose and demonstrate a front-light structure to improve the fluorescence observation performance of a lensless fluorescence imaging device. A thin front-light structure is inserted between the object to be observed and the emission filter. This enables the irradiation of excitation light from the same side as the lensless imaging device. We fabricated a front-light structure by patterning diffraction gratings on a thin glass and combined it with a high-performance emission filter to obtain a fluorescence imaging device, which facilitates fluorescence observation as well.

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